Janice Yamanaka

Misleading Axis on Graphs

Good data visualization seems to be utilitarian in a way, perhaps devoid of taste and style.  But after reading the intro to this essay, and after our discussion today, I feel that we all come equipped with a ‘point of view’ – as a designer and a viewer. We can't help it.

I can think of a handful of friends who are artists who don’t ‘get’ conceptual art, don’t enjoy it, and don’t seek it out.  I also have a handful of artist friends who are conceptual art snobs.  How we create and ‘look’ at art or life, or visualizations depends on your point of reference.  

Like everything else in life, visuals are sometimes a shell game.  You can dress up, or dupe the viewer into believing that the graphic is meaningful, as we discussed with the ‘Monstrous’ visualization.

I think that we all as part of our human conditioning, seek order to mine specific meaning.  But in order to have your data read, do we sacrifice order for viewability?  Do we worry about the form in which the data will take, at the risk of not selling the message to be compelling?   Or is the viewability a way to get more views, therefore more data or thought is provocative?

Another part of this essay that was thought-provoking was the meaning of ‘outlier’ data skewing results.  I’ve always believed (and read the Malcolm Gladwell book ‘Outliers’) that outliers create and can tease out innovation.  The use of outliers in data seems to be a throwaway.  But doesn’t that go against a value that may mean creativity, trend or innovation?

Misleading Axis on Graphs

This essay seems to be a discussion of how the ‘x’ and ‘y’ axis can be manipulated to a satisfying result.  But this is the function, and responsibility of the designer.  There is a moral obligation to show the data, no matter how far away it may go from your hypothesis.  This essay is self explanatory, but I’m not so sure that again, we all come into a design with a point of view, a skew, and an aesthetic.  

It may be impossible, although not entirely truthful to be swayed by either the data, or creating the visualization.  An example I can give is the genre of Documentary films. There is editing, camera view, light, as well as dialogue and visuals that can skew the information.

The Principle of Proportional Ink

The essence of this essay is that the amount of information being shown, should be proportional to the amount of ink being used.  But in the above essay (Misleading Axis on Graphs), line graphs use ‘hierachy’ of height to show data.  This argues, to me, the logic of this principle.

Bar graphs, line graphs, bubble charts, donut bar graphs , changing denominator (the Time magazine example),  the use of 3 dimensional graphics (in bar and piecharts) are discussed in depth.

It’s a compelling case to be made in order for the data to be important it needs the most ink, but I’m unclear if the goal is to show the value of 0 (crime, rapes, deaths), our eyes do not necessary associate ‘less’ as more.  

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